Information management systems often utilize models to characterize managed information in order to facilitate the processing of queries directed to that information. The complexity of such models generally depends on the type of system, and the complexity compounds as multiple independent systems leverage their own instances of this information, usually in a different modeled form. For example, single-model, single-entity (SMSE) systems are readily characterizable by a particular model, consistent among participating systems, specifically for the use in managing a given entity. In systems of this type, issues such as upgrades, backward compatibility, forward integration, information contracts, access control, and compliance can be addressed in a straightforward manner using conventional techniques across a multitude of system boundaries.
Additional complexity is introduced in multi-model, single-entity (MMSE) systems, which typically need to incorporate functionality for transforming from one modeled foam to another. For example, the models may differ in terms of the manner in which particular attributes are represented or linked. Issues such as those identified above that are straightforward to deal with in SMSE systems can cause the number of model versions required in an MMSE system to increase exponentially. This can have a negative impact on query processing efficiency and system throughput performance.
Such problems are magnified in multi-model, multi-entity (MMME) systems, in which hierarchical entity domains bring another exponential increase in complexity. The hierarchical relationships in such systems introduce additional issues such as directional navigability and multiple inheritance.
There are a number of known approaches to model version complexity reduction, typically involving version control strategies. For example, these strategies may include backward compatibility limitations as well as attribute decomposition to reduce variance between models. However, such complexity reduction techniques do not adequately address the substantial increase in complexity associated with MMSE and MMME systems.
In information management systems involving semantically modeled data, the above-noted models may make use of the Resource Description Framework (RDF) of the World Wide Web Consortium (W3C). RDF is a language for representing information about resources in the web. It identifies such resources using Uniform Resource Identifiers (URIs) and models statements about the resources as a directed graph. A given such statement is represented by the elements (Subject, Predicate, Object), also referred to as an RDF triple.
Additional details regarding RDF are described in the following W3C Recommendations, all dated Feb. 10, 2004 and incorporated by reference herein: RDF/XML Syntax Specification (Revised); RDF Vocabulary Description Language 1.0: RDF Schema; RDF: Concepts and Abstract Syntax; RDF Semantics; and RDF Test Cases. See also W3C Recommendation RDFa in XHTML: Syntax and Processing, Oct. 14, 2008, which is also incorporated by reference herein.
It is also known to incorporate context information into models based on RDF. See, for example, S. Decker et al., “TRIPLE—an RDF Rule Language with Context and Use Cases,” W3C Workshop on Rule Languages for Interoperability, 27-28 Apr. 2005, Washington, D.C., USA; and A. Billig et al., “Platform Independent Model Transformation Based on Triple,” Lecture Notes in Computer Science, Vol. 3231, pp. 493-511, 2004.
However, these techniques fail to provide a scalable approach that is suitable for significantly reducing model version complexity, particularly in MMSE and MMME information management systems.